The 12th International Symposium on Wireless Personal Multimedia Communications (WPMC’09)
Invited paper
USER BASED ADAPTIVE JOINT CHANNEL ASSIGNMENT IN MULTI-CELL
OFDMA SYSTEMS
Wenting Li, Chen Wang and Meixia Tao
Department of Electronic Engineering
Shanghai Jiao Tong University, Shanghai, China
Emails: {liwentingangle, mxtao}@sjtu.edu.cn ∗
A BSTRACT
This paper considers coordinated scheduling in multi-cell
OFDMA systems. We propose a user-based adaptive joint
channel assignment scheme. In the proposed scheme, all the
cell-edge users from multiple cells are scheduled jointly while
cell-centre users are scheduled in each individual cell. The
method exploits both multi-user diversity and frequency diversity. It avoids the dominant inter-cell interference via the socalled Assignment Table. To apply the algorithm in a large coordination set, a cell grouping method together with a group coordination method is also introduced. Simulation results show
that the proposed scheme can increase considerably the average
cell throughput compared with existing inter-cell interference
coordination schemes.
I
I NTRODUCTION
Orthogonal frequency division multiplexing (OFDM) has become a leading candidate to provide higher and higher data access capability in future cellular systems. With OFDM, a wideband frequency-selective fading channel can be divided into a
set of orthogonal narrowband subchannels. OFDM can thus
overcome inter-symbol interference (ISI) and offer good design flexibility. Furthermore, since different subchannels can
be assigned to different users, the OFDM technique naturally
provides a multiple-access method, as known as OFDMA. By
adaptively allocating the subchannels among multiple users according to their channel state information, multi-user diversity
can be exploited. For these advantages, OFDMA has been
adopted in 3GPP Long Term Evolution (LTE) downlink and
IEEE 802.16e, and it will continue to be the fundamental technique for future advanced cellular systems. Though having immunity to intra-cell interference thanks to the subchannel orthogonality, OFDM however cannot eliminate the inter-cell interference (ICI) in multi-cell scenarios. To mitigate the ICI and
hence to further improve the system performance, coordination
among neighboring cells is necessary.
Several scheduling and resource allocation techniques for
multi-cell OFDMA systems have been proposed to mitigate
ICI in the literature. In [7], Li and Liu propose a two-level
resource allocation scheme, where RNC (Radio Network Controller) solves the network planning problem in the first level
and BS (base station) solves the cell throughput maximization
problem in the second level. However this scheme is too complex to be practically feasible. A low-complexity approach us∗ This work is sponsored in part by the Doctoral Fund of Ministry of Education of China (No. 200802481002) and by DOCOMO Beijing Labs.
ing graph theory is adopted in [3]. However it assigns only one
channel to each user. In the current LTE systems, two practical
ICI coordination schemes, fractional frequency reuse (FFR) [2]
and soft frequency reuse (SFR) [6], have been proposed. Both
schemes are based on the idea of having a frequency reuse
factor of one in cell centre areas and a higher reuse factor in
cell edge areas. However, being a static frequency assignment
scheme, neither FFR or SFR can fully exploit the inherent frequency diversity gain in OFDM systems.
Recently, a new concept, namely, Coordinated Multiple
Point (CoMP) transmission and reception [4], is being discussed in LTE-Advanced systems to further reduce ICI and
improve the overall spectrum efficiency per cell. With CoMP,
multiple geographically separated cells are coordinated by a
central unit and share necessary information such as user data,
channel state information (CSI) and scheduling information.
According to the information each cell shares, CoMP technology can be categorized into two types: coordinated scheduling and joint processing. In coordinated scheduling, user data
is only available at its serving cell, while in joint processing,
both user data and CSI need to be exchanged at each point in
the coordination set. In this paper we focus on coordinated
scheduling, which has less impact on the system structure than
joint processing does. In [5], a fast cell selection method is
proposed for coordinated scheduling. Therein, the scheduling
is jointly executed among all the users within the cooperating
cells. As a result, the computational complexity as well as signalling overhead are very high.
In this paper we propose a new coordinated scheduling
method for downlink multi-cell OFDMA systems, called userbased adaptive joint multi-cell channel assignment. Different from the fast cell selection method in [5], the proposed
scheme schedules only cell edge users jointly while cell-centre
users are scheduled in each individual cell. Compared with
the existing FFR and SFR schemes, the proposed scheme is
user based. That is, at each scheduling interval, a user is selected to choose its preferred subchannel from the available
resource pool. Thus, both frequency diversity and multi-user
diversity can be exploited. Two novel terminologies are introduced in our joint multi-cell channel assignment, Assignment
Table (to indicate the channel-to-user assignment result and to
avoid the dominant interference) and User-channel List (to determine the next user for resource assignment). To apply the
algorithm in a large coordination set, we further propose a cell
grouping method. With this method, the multiple cooperating
cells are divided into smaller cooperating groups based on their
geographical locations. Then, the proposed user-based adaptive joint multi-cell channel assignment algorithm is adopted
The 12th International Symposium on Wireless Personal Multimedia Communications (WPMC’09)
in each individual group sequentially. The resulting scheduling information associated with cell-edge users from a previous
group is passed on to next groups in the order of scheduling.
The rest of the paper is organized as follows. In Section II,
we briefly discuss the existing FFR and SFR schemes as preliminaries. The proposed user-based coordinated scheduling
scheme is presented in Section III. Section IV introduces the
cell grouping method, followed by simulation results in Section V. Finally we conclude this paper in Section VI.
II
P RELIMINARIES ON I NTER - CELL I NTERFERENCE
C OORDINATION
In this section we briefly introduce the two existing ICI coordination schemes in LTE systems, namely FFR and SFR.
Their performances will be compared with that of the proposed
scheme in Section V.
FFR was first proposed for GSM networks. Its main idea
can be illustrated in Fig. 1, where the whole spectrum is divided into two bands. Band A is reserved for cell-centre users
and Band B is for cell-edge users. To avoid ICI, band B is further divided into three non-overlapping sub-bands, one for each
adjacent cell. As one can see, each user is only eligible to access a fractional frequency band. In specific, cell-centre users
can only be assigned channels within the 1/2 band, and celledge users within the 1/6 band. Therefore, the FFR scheme
cannot fully exploit the frequency diversity. In addition, from
the perspective of cell-edge region, FFR avoids ICI completely
but with the cost of higher frequency reuse factor.
Cell edge band
Cell center band
B
Cell 1
Cell 1
Cell 3
Cell 2
A
Pedge
Pcenter
Cell 2
Cell 3
Figure 1: Fractional frequency reuse (FFR).
The SFR scheme is illustrated in Fig. 2. Here, 1/3 of the
whole spectrum is reserved for cell-edge users and is nonoverlapping among the neighboring cells. When the cell edge
frequency band is not fully occupied by the cell edge users, it
can be re-assigned to cell-centre users. A power amplification
factor β is introduced, which denotes the ratio of the transmission power level on cell centre band to the transmission power
level on cell edge band. Notice that, compared with FFR, SFR
can exploit higher frequency diversity and hence is expected to
achieve better system throughput.
III
P ROPOSED C OORDINATED S CHEDULING
We first introduce the signaling overhead among the coordination set, then describe the channel assignment method in detail.
III.A Signaling in a super-cell
Assume that the multiple cooperating cells are coordinated by
a central unit, named super-cell. The signalling information in
Invited paper
Cell edge band
Cell center band
Cell1
Cell 1
Pedge
Pcenter
Cell 2
Cell 3
Cell 2
Cell 3
Figure 2: Soft frequency reuse (SFR).
the super-cell required by our proposed coordinated scheduling
method is described in the following.
a) Feedback from UE to its serving BS:
• SINR (signal-to-interference and noise ratio) on each subchannel;
• Cell ID of the strongest interfering BS on each subchannel;
• Information for UE classification, e.g. large scale fading.
b) Feedback from BSs to the super-cell:
• Available sub-channel index;
• SINR of its cell-edge UEs on the available sub-channel;
• The strongest interfering Cell ID of its cell-edge UEs on
the available sub-channels;
• Own cell ID.
c) Signaling from the super-cell to BSs: the scheduling information
regarding all the cell-edge users.
III.B ICI avoidance rule: Assignment Table
In our scheme, it is assumed that each BS is equipped with an
omni-directional antenna. Similar to SFR, it is also assumed
that the transmit power level to cell-centre users is lower than
that of cell-edge users and their ratio is given by β. Therefore,
the ICI caused by the centre users in one cell to the neighboring
cells can be ignored. In the following we introduce the channel
assignment rule that avoids the ICI caused by edge users.
As mentioned in Section III.A, each user needs to feed back
its serving cell the Cell ID of the strongest interfering BS on
each available sub-channel. Such information is used to avoid
the dominant interference. An Assignment Table is defined to
indicate the channel-to-user assignment result. Consider the
table value associated with channel k and user m. It is defined
as follows:
(
0
1
−1
= the channel is available to the user;
= the channel is assigned to the user;
= the channel is not available to the user.
Once a channel is assigned, this Assignment Table will be
updated. Suppose channel k is assigned to user m of cell i,
then the Assignment Table is updated as follows:
a) Set the Table value associated with channel k and user m of cell
i to 1, the values with all the other users in this cell on the same
channel to −1;
b) If user m is a cell-edge user, the values associated with all the
cell-edge users belonging to the strongest interfering cell of user
m on channel k are set to −1. This is because the neighbor cell
who dominates the interference to the edge user m cannot use
this channel anymore;
The 12th International Symposium on Wireless Personal Multimedia Communications (WPMC’09)
c) If the transmission on channel k from cell i dominates the interference to some cell-edge users in other neighboring cells, then
these users cannot occupy channel k and the corresponding values are set to −1 in the Assignment Table.
4
5
B
3
1
A
6
2
9
7
C
8
Figure 3: An example of multi-cell user distribution.
Note that the interference from other cells to the cell-centre
users can be ignored in the system, so only Step a) needs to
be considered when we assign the channel for the cell-centre
users. In the following we give a simple example to illustrate
this process in more details. Suppose that there are 4 channels, 3 cells with one cell-edge user and two cell-centre users
in each. The distribution of users is shown in Fig. 3, where user
1, 2, 4, 5, 7, and 8 are all cell-centre users while user 3, 6, 9 are
cell-edge users of cell A, B, and C, respectively.
Suppose that after some steps, the Assignment Table is given
in Table 1, and the strongest cell ID is illustrated in Table 2.
From Table 2, we can see that for user 3 the strongest interference on channel 1 comes from cell C. That is to say on channel
1, cell C dominates the interference to user 3. From Table 2, it
is observed that cell C dominates the interference to user 6 on
channel 4, if we assign the channel 4 to user 6, the cell C can
only assign channel 4 to its centre users. Meanwhile, since cell
B dominates the interference to user 3 on channel 4, channel
4 is not available to user 3. Therefore, the Assignment Table
should be updated as shown in Table 3.
Through the Assignment Table, the dominant interference is
avoided completely. The Assignment Table is crucial to the
coordination of the different groups of cells too, as will be detailed in Section IV.
Table 1: Assignment Table
user Cell A
channel 1 2 3
4
Cell B
5 6
7
Cell C
8 9
1
0
0
0
-1
1
-1
0
0
0
2
1
-1
-1
0
0
0
-1
1
-1
3
-1
1
-1
1
-1
-1
0
0
0
4
0
0
0
0
0
0
0
0
0
Table 2: Strongest Cell ID of cell-edge users
channel
user
3
6
9
1
2
3
4
C
other
B
other
other
B
other
other
other
B
C
other
III.C Scheduling method
In our scheme a User-channel List is adopted to exploit both
user and frequency diversity by pooling all the cell-edge users
Invited paper
Table 3: Updated Assignment Table (1)
user
Cell A
channel 1 2 3
4
Cell B
5 6
7
Cell C
8 9
1
-1
-1
1
-1
1
-1
0
0
-1
2
1
-1
-1
0
0
0
-1
1
-1
3
-1
1
-1
1
-1
-1
0
0
0
4
0
0
-1
-1
-1
1
0
0
-1
from multiple cells together and jointly allocating them the
sub-channels from the entire frequency band based on instantaneous channel conditions. The User-channel list is formed
by sorting all cell-edge (centre) users by their channel gains
on each channel in descending order. The channel gains are
evaluated by the SINR (signal-to-interference and noise ratio)
excluding the strongest interference, which is defined as:
pmki
,
(1)
SINRmki = 2 P
σ + j6=i pmkj − pmkd
where the pmki denotes the receiving power of user m from its
serving cell i on channel k, pmkj denotes the receiving power
of user m from its neighbour cell j on channel k, pmkd denotes
the receiving power of user m on channel k from its strongest
neighbour cell d, and σ 2 is the noise power.
The channel assignment will be executed according to the
User-channel List. Once a channel is assigned, suppose assign
channel k to cell-edge user m of cell i, the User-channel List
will be updated as follows.
a) Since the other users in cell i cannot use channel k, the corresponding elements in User-channel List will be deleted;
b) Since the neighbor cell who dominates the interference to celledge user m in cell i cannot use this channel anymore, the elements associated with all the cell-edge users belonging to this
neighbor cell at this channel will be deleted;
c) If the transmission on channel k from cell i dominates the interference to some cell-edge users in other neighboring cells, then
these users cannot occupy channel k and the corresponding elements will be deleted.
Note that during the assignment for the cell-centre users,
only Step a) needs to be considered for that the interference
from the neighbor cell to cell-centre users can be ignored. Also,
while updating the User-channel List, the Assignment Table
shall be updated accordingly as described previously.
III.D Algorithm Procedure
The complete algorithm procedure is outlined as follow:
1) User classification: for each cell, divide all the active users into
two groups: cell-edge users and cell-centre users, using large
scale fading.
2) For each cell, assign channels to cell-centre users. The flow chart
is given in Fig. 4. Here, nmax,c denotes the maximum number
of sub-channels assigned to cell-centre user, which is predefined
to prevent some users occupying resources greedily.
3) Jointly assign channels to all cell-edge users in the coordinating
cells, with flow chart given in Fig. 5. Here nmax,e is the maximum number of sub-channels assigned to cell-edge user, and
nmin is defined to guarantee the QoS for each user.
The 12th International Symposium on Wireless Personal Multimedia Communications (WPMC’09)
4) For each cell, assign the remaining channels to centre users:
(i) Compute the total number of channels that are not occupied by cell-edge users in each cell, and denote it by NR .
(ii) LetNc,max = dNR /Nin e, where Nin denotes the number of centre users in the cell. Then Nc,max is used as the maximal channel number per centre user.
(iii) Assign the remaining channels to the centre users using
the same method as Step 2), with the difference that the maximal
channel number is Nc,max , instead of nmax,c .
Invited paper
Sort all cell-edge users in the coordinating cells
by their sub-channel gains in descending order
to form the user-channel list
Find the first user in the User List and check
the number of channels it has occupied a
priori, denoted as m
m< n m a x, c
Yes
Delete this user
from the User List
No
Assign the channel for the 1st user
For each cell, divide all the active users into two
groups: cell-edge users and cell-center users.
Update the user-channel list
Update the Assignment Table
Find the first user in the User List and check the
number of channels it has occupied a priori,
denoted as m
Delete this user
from the User List
m < nmax,c
Yes
Is there any element left
in the User-Channe List
No
Yes
Assign the channel for the 1st user
No
Search the edge-users which occupy less
than nminchannels, discard these users,
and update the assignment table
Update the user-channel list
Update the Assignment Table
Yes
The centre user channel
condition (S) better than T?
Figure 5: The algorithm flow chart of step 3.
1 and Group 3 are both composed by three parts, and each part
contains 3 cell sites. Due to spatial separation, the intra-group
interference among the cells in different parts can be ignored.
Thus, no signalling exchange is required among these cells.
No
Step 3
S: the SINR of the present element in the User-channel list
T: the predefined threshold based on the SINR of cell-edge users
Figure 4: The algorithm flow chart of step 2.
The above algorithm assigns channels to cell-centre users
and hence is named as “centre-first”. If we reverse the order
of step 2 and step 3, a higher priority will be given to celledge users and we thus obtain the “edge-first” version. In the
“edge-first” scheme, cell-edge users can expect to enjoy higher
degree of freedom when choosing their preferred sub-channels.
Nevertheless, if cell-edge users dominate the network, one may
switch back to the “centre-first” scheme to avoid the case that
all the channels may be solely assigned to cell-edge users. The
selection of the two schemes can be adaptive with respect to
the ratio of cell-edge users and cell-centre users.
IV
C ELL G ROUPING
To apply the proposed user-based adaptive joint multi-cell
channel assignment schemes in practical systems, the computational complexity as well as signalling overhead need to be
considered. In this section we propose a grouping method to
reduce the complexity and overhead. Take the typical 19-cell
hexagonal cellular configuration as an illustrative example. We
divide the 19 cell sites into 3 groups as shown in Fig. 6. Group
Group 1
Group 2
Group 3
Figure 6: Cell grouping.
With the above grouping, we apply the proposed channel assignment algorithm in each individual group sequentially. Take
the order of “Group 1 → Group 3 → Group 2” for example.
Group 1 performs the channel assignment as if there was no
interference from other groups. Then, Group 1 informs other
groups about the resulting Assignment Table associated with
cell-edge users. Upon receiving this Table, Group 3 initializes
its own channel Assignment Table by taking into account such
prior information. The same coordinated scheduling algorithm
is then applied in Group 3, and the resulting Assignment Table associated with cell-edge users is sent to Group 2. Clearly,
the scheduling order of the groups will affect the performance
of each group. To maintain cell fairness, the order of the next
scheduling interval can be Group 3 → Group 2 → Group 1,
and followed by Group 2 → Group 1 → Group 3.
The 12th International Symposium on Wireless Personal Multimedia Communications (WPMC’09)
The scheduling order of the groups can be adaptive with respect to the cell load. If a certain cell is heavily loaded, for example there are too many edge users, the corresponding group
will get the priority to be scheduled first.
Invited paper
The CDF of user throughput
1
0.8
S IMULATION RESULTS
CDF
0.6
V
0.4
VI
C ONCLUSION
We have proposed a user-based adaptive joint channel assignment scheme for downlink multi-cell OFDMA systems. The
scheme performs joint channel assignment for cell-edge users
from multiple cells, while assigning channels for cell-centre
user in each individual cell. The total throughput is improved
by the user-channel list, which can exploit both frequency
diversity and multi-user diversity. The assignment table is
adopted to avoid the dominant interference. To make the algorithm more feasible in practical systems, a cell grouping
method and a corresponding group coordination method are
proposed. The simulation results show that the proposed algorithms can achieve higher average throughput per sector. The
worst 5% user throughput can also be improved under certain
conditions.
Proposed Edge-first
Proposed Centre-first
0.2
FFR
SFR
0
0
2
4
6
bps/Hz
8
10
12
Figure 7: CDF of user throughput for β = 0.5.
Table 4: Sector and User Throughputs for β = 0.5
Scheme
FFR
SFR
Edge-first
Centre-first
Average sector
throughput (Mbps)
20.81
(0%)(-)
24.17
(-)(0%)
27.02
(29.8%)(11.8%)
25.49
(22.5%)(5.5%)
5% (bps/Hz)
0.667
(0%)(-)
0.705
(-)(0%)
0.665
(-0.3%)(-5.7%)
0.655
(-1.8%)(-7.1%)
The CDF of user throughput
1
0.8
0.6
CDF
The simulation setting is based on LTE specifications [1]. To
classify if a user belongs to cell center or cell edge, we set 3dB
as the threshold for the difference on large scale fading between
the serving cell and the strongest neighboring cell.
Fig. 7 compares the cumulative distribution function (CDF)
of user throughput in different schemes at power ratio β =
0.5. The average throughput per sector as well as the 5%throughput performance are given in Table 4. From these results one can see that the proposed multi-cell channel assignment schemes (with both “edge-first” and “centre-first”) provide higher average throughput per sector than conventional
FFR and SFR. This is expected as the proposed scheme is userbased and exploits both frequency and multi-user diversity. As
for the worst 5% user throughput, it is seen that the proposed
“edge-first” scheme almost maintains the performance compared with the FFR scheme. The “centre-first” scheme performs slightly worse as expected. Among all the schemes, the
existing SFR achieves the best 5%-throughput performance, for
it can exploit high frequency diversity gain for edge users and
yet have no ICI from cell-centre users to cell-edge users.
Fig. 8 and Table 5 show the results when the power ratio is changed to β = 0.6. One can see that increasing the
power ratio to 0.6 does not affect the overall distribution of
user throughput much. This is because increasing the transmit power to cell-centre users also causes more interference to
neighboring cells. However, the 5%-throughput performances
change a lot when increasing β. In specific, the performance of
SFR degrades, while the performance of the proposed “edgefirst” scheme is enhanced, as shown in Table 5. This is because the worst 5% users in the simulation for the “edge-first”
scheme are not always from the cell-edge users defined in our
algorithm. Instead, cell-centre users dominates the worst 5%throughput. As a result, increasing the transmit power to cellcentre users improves the 5%-throughput performance.
0.4
Proposed Edge-first
Proposed Centre-first
FFR
SFR
0.2
0
0
2
4
6
bps/Hz
8
10
12
Figure 8: CDF of user throughput for β = 0.6.
Table 5: Sector and User Throughputs for β = 0.6
Scheme
FFR
SFR
Average sector
throughput (Mbps)
20.81
(0%)(-)
24.64
(-)(0%)
27.44
25.86
(31.9%)(11.4%) (24.35%)(5.0%)
5% (bps/Hz)
0.666
(0%)(-)
0.654
(-)(0%)
0.676
(0.15%)(3.4%)
Edge-first
Centre-first
0.651
(-2.3%)(-0.5%)
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